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Record W6943889530 · doi:10.17605/osf.io/shfjg

Scoping review to assess the effectiveness of government-funded and population-based physical activity initiatives in Australia.

2023· other· en· W6943889530 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthGovernment (linguistics)Population healthHealth promotionPhysical activityAction planWelfareHealth policyAction (physics)

Abstract

fetched live from OpenAlex

The health benefits of physical activity play a vital public health role in the prevention and management of chronic disease and other health conditions (Halpin, Morales-Suárez-Varela & Martin-Moreno 2010; Thornton et al. 2016). Unfortunately, less than half of Australians are meeting the recommended physical activity level. (Australian Institute of Health and Welfare [AIHW] 2021). As such, there is a need for population-based approaches that can reach many Australians affordably and effectively. Government agencies commonly use evidence-based practice to improve public health outcomes (Titler 2008), and a scoping review will be conducted to examine government-funded population-based physical activity initiatives to understand their impacts, methods, gaps, and limitations. Moreover, we will gain extensive knowledge about the physical activity initiatives carried out in Australia and how they have been evaluated. Therefore, this scoping review will explore the effectiveness of government-funded population-based physical activity initiatives in Australia. References: Australian Institute of Health and Welfare (AIHW) 2021a, Australian Burden of Disease Study 2018: Interactive data on risk factor burden, viewed 03, June, 2022, https://www.aihw.gov.au/reports/burden-of-disease/abds-2018-interactive-data-risk-factors/contents/physical-inactivity Halpin, HA, Morales-Suárez-Varela, MM & Martin-Moreno, JM 2010, 'Chronic disease prevention and the new public health', Public Health Reviews, vol. 32, no. 1, pp. 120-154. DOI: 10.1007/BF03391595. SA Health 2022a, Wellbeing SA, viewed 08, August,2022, https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/wellbeing+sa/wellbeing+sa SA Health 2022b, The Physical Activity in Nature Action Plan 2021-2024, viewed 04,June,2022, https://www.sahealth.sa.gov.au/wps/wcm/connect/ South Australian Population Health Survey (SAPHS) 2019, Annual report 2020 - Adults, viewed 10 September 2022, https://das7nagdq54z0.cloudfront.net/downloads/SAPHS/SAPHS-2020-Annual-Report-Adults.pdf Thornton, JS, Frémont, P, Khan, K, Poirier, P, Fowles, J, Wells, GD & Frankovich, RJ 2016, 'Physical activity prescription: a critical opportunity to address a modifiable risk factor for the prevention and management of chronic disease: a position statement by the Canadian Academy of Sport and Exercise Medicine', British journal of sports medicine, vol. 50, no. 18, pp. 1109-1114. DOI: 10.1136/bjsports-2016-096291.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.101
metaresearch head score (Gemma)0.309
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.899
Threshold uncertainty score0.535

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1010.309
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0110.012
Bibliometrics0.0320.029
Science and technology studies0.0030.003
Scholarly communication0.0090.008
Open science0.0050.007
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0130.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.121
GPT teacher head0.468
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainEvaluation
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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